Make Data Literacy a Top Priority of Your Organization to Stay Alive

Make Data Literacy a Top Priority of Your Organization to Stay Alive2018-01-122018-09-18https://www.inteliment.com/wp-content/uploads/2018/08/white_logo-2.pngInteliment Technologieshttps://www.inteliment.com/wp-content/uploads/2018/01/b-24-f.jpg200px200px

The value and importance of data is well appreciated and accepted today. Gone are the days of decision-making based on “gut-feeling”. Today, it’s the age of “data-driven” decisions. It also means that organizations need to equip people at all the levels with sufficient tools and data to help them carry on the business in a data-literate way.

Understanding Data Literacy

Data literacy is a core attribute of large, modern business enterprises. This stems from the fact that contemporary business processes are generating huge volumes of data and digital information. Experts state that data literacy defines the “the ability to derive meaningful information from data, interpreting data visualizations such as graphs and charts, and thinking critically about information yielded by data analysis.”
In addition, data literacy hinges on a basic ability in mathematics, statistics, and analytics. Further, data literacy centers on the domains of data, analytics, decision science, and digital. Companies and enterprises have realized the value of data literacy in making sense of movements and developments in modern markets. This has prompted them to institute the role of the Chief Data Officer. This individual is instrumental in using data analytics tools and helping to identify and assess trends in the market based on the underlying data.
In this post, we will examine some of the trends –

Stages of Data Literacy

Corporate organizations need to collect data and feed it into a computer or information processing system. This stage is primary and enables the business to survey the information through electronic means. After coding the information, multiple statistical techniques are applied to the data. This action enables data scientists to discover various categories of relationships between discrete elements in a data set. Following this, the data can be analyzed qualitatively or quantitatively in a bid to generate business insights. It is important that brands and businesses encourage some form of data literacy across multiple levels of the commercial and business organization.

This is critical in modern business because “most companies recognize data in the hands of a few data experts can be powerful, but data at the fingertips of many is what will be truly transformational.”

Data-driven behaviors

Digital data and real world information are melded to create data-driven behavior in corporate domains. Corporate captains and business managers need to put in place the tools and infrastructure that empower employees to pull insights from data. These initiatives should also encourage data literacy. Marketing teams, for instance, can pull ‘click streams’ and ‘social data’ from the global Internet in a bid to assess the health of a marketing campaign. The data will likely point to success in certain aspects of a campaign; it may also spotlight deficiencies and gaps that can be tuned to boost campaign outcomes. Different variables, such as various aspects of customer behavior, the reaction of the market, data outliers, and test results may emerge to add color to the data interpretation. The marketing strategists may also discover and unearth new insights based on the collected data. These streams of derivative information can help the business enterprise to create efficient future campaigns.

Decisions based on data

A data-first business stance allows businesses to tune out distractions and arrive at correct business decisions. This is important because McKinsey reckons that “an estimated 90% of the digital data ever created in the world has been generated in just two years, yet only 1% of that data has been analyzed.”

This indicates that the ‘mountains of business data’ are growing much faster than our ability to derive insight from such data. Consequently, business organizations are moving to draw real world meaning from vast streams of digital data. Top-level executives have indicated the intent to drive strategic business decisions based on data analytics, instead of relying solely on experience and intuition because the former tends to deliver better and concrete results. This view is bolstered by the fact that modern data analytics can create a range of descriptive, diagnostic, predictive, and prescriptive actions. The range of outcomes expands when we note that modern businesses can apply data analytics to rectangular datasets, databases, images, text, streaming data, and audiovisual information. This is significant because some experts estimate that “the combined market of Big Data and business intelligence may reach $203 billion by 2020.”

Implementing data literacy

Commercial organizations that remain serious about their markets should move to institute data literacy programs for their staff members. This stance can originate in ‘data boot camps’ that quickly bring staff members up to speed on data analysis and data interpretation techniques. A week-long course can help employees at all levels to familiarize themselves with the basics of data science. They are trained to analyze data and act on the information. The outcomes of this action empower staff members to gain exposure to a diverse set of data procedures. Subsequently, employees can apply their learnings to their work processes.

In light of the above, I strongly feel that modern business enterprises must invest in data literacy. Business luminaries and the corporate leadership must be not only made aware of its benefits but also must be mentored and tutored about the numerous benefits of data-driven decisions and how those have paid off in terms of differentiation, insights, innovation, risk mitigation, etc. These actions can lead to new business paradigms that are powered by real-world data and information generated from business and client interactions.

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